文献类型：期刊文献

中文题名：Future vehicles:learnable wheeled robots

作者：Deyi LI[1];Nan MA[2,3];Yue GAO[4]

第一作者：Deyi LI

机构：[1]Academy of Military Science,Beijing 100036,China;[2]Beijing Key Laboratory of Information Service Engineering,Beijing Union University,Beijing 100101,China;[3]College of Robotics,Beijing Union University,Beijing 100101,China;[4]School of Software,Tsinghua University,Beijing 100084,China

第一机构：Academy of Military Science,Beijing 100036,China

年份：2020

卷号：63

期号：9

起止页码：245-252

中文期刊名：中国科学：信息科学（英文版）

收录：Scopus;CSCD:【CSCD2019_2020】；

基金：National Natural Science Foundation of China(Grant Nos.61871038;61931012);Beijing Natural Science Foundation(Grant No.4182022);Major project of Beijing Social Science Foundation(Grant No.18ZDA09)。

语种：英文

中文关键词：wheeled robots;driving brain;swarm intelligence;negative learning;data-driven self-learning

摘要：As one of the important signs of the third wave of artificial intelligence,wheeled robots not only inherit knowledge but also learn independently,which brings about to learnable wheeled robots that use a driving brain to achieve data-driven control and learning.Presently,most existing technologies for selfdriving vehicles can learn positively from the benchmark drivers to guarantee safe driving.However,in many unpredicted situations,such as rollover,human drivers often cause the behavior of irrational subconscious on account of human emotions like panic.In this paper,we propose a learnable wheeled robot using the driving brain by taking the rollover as an example,which is the most serious and dangerous situation in dynamic vehicle operations.Then,based on the analysis of rollover accidents,we utilize the driving brain reversely and conduct negative learning,materializing,and condensing the group intelligence of accident experts,to solve the problem of the lack of individual intelligence in emergencies and further promote real-time response to other dangerous conditions,such as puncture for self-driving vehicles.